Essec\Faculty\Model\Contribution {#2216 ▼
#_index: "academ_contributions"
#_id: "13982"
#_source: array:26 [
"id" => "13982"
"slug" => "13982-we-modeled-long-memory-with-just-one-lag"
"yearMonth" => "2023-09"
"year" => "2023"
"title" => "We modeled long memory with just one lag!"
"description" => "BAUWENS, L., CHEVILLON, G. et LAURENT, S. (2023). We modeled long memory with just one lag! <i>Journal of Econometrics</i>, 236(1), pp. 105467. 
BAUWENS, L., CHEVILLON, G. et LAURENT, S. (2023). We modeled long memory with just one lag! <i>Journ "
"authors" => array:3 [
0 => array:3 [
"name" => "CHEVILLON Guillaume"
"bid" => "B00072304"
"slug" => "chevillon-guillaume"
]
1 => array:1 [
"name" => "BAUWENS Luc"
]
2 => array:1 [
"name" => "LAURENT Sebastien"
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Bayesian estimation"
1 => "Ridge regression"
2 => "Vector autoregressive model"
3 => "Forecasting"
]
"updatedAt" => "2024-03-18 10:52:40"
"publicationUrl" => "https://doi.org/10.1016/j.jeconom.2023.04.010"
"publicationInfo" => array:3 [
"pages" => "105467"
"volume" => "236"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Two recent contributions have found conditions for large dimensional networks or systems to generate long memory in their individual components. We build on these and provide a multivariate methodology for modeling and forecasting series displaying long range dependence. We model long memory properties within a vector autoregressive system of order 1 and consider Bayesian estimation or ridge regression. For these, we derive a theory-driven parametric setting that informs a prior distribution or a shrinkage target. Our proposal significantly outperforms univariate time series long-memory models when forecasting a daily volatility measure for 250 U.S. company stocks over twelve years. This provides an empirical validation of the theoretical results showing long memory can be sourced to marginalization within a large dimensional system. Two recent contributions have found conditions for large dimensional networks or systems to generate "
"en" => "Two recent contributions have found conditions for large dimensional networks or systems to generate long memory in their individual components. We build on these and provide a multivariate methodology for modeling and forecasting series displaying long range dependence. We model long memory properties within a vector autoregressive system of order 1 and consider Bayesian estimation or ridge regression. For these, we derive a theory-driven parametric setting that informs a prior distribution or a shrinkage target. Our proposal significantly outperforms univariate time series long-memory models when forecasting a daily volatility measure for 250 U.S. company stocks over twelve years. This provides an empirical validation of the theoretical results showing long memory can be sourced to marginalization within a large dimensional system. Two recent contributions have found conditions for large dimensional networks or systems to generate "
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2025-04-09T21:21:43.000Z"
"docTitle" => "We modeled long memory with just one lag!"
"docSurtitle" => "Journal articles"
"authorNames" => "<a href="/cv/chevillon-guillaume">CHEVILLON Guillaume</a>, BAUWENS Luc, LAURENT Sebastien"
"docDescription" => "<span class="document-property-authors">CHEVILLON Guillaume, BAUWENS Luc, LAURENT Sebastien</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2023</span> <span class="document-property-authors">CHEVILLON Guillaume, BAUWENS Luc, LAURENT Sebastien</span><b "
"keywordList" => "<a href="#">Bayesian estimation</a>, <a href="#">Ridge regression</a>, <a href="#">Vector autoregressive model</a>, <a href="#">Forecasting</a> <a href="#">Bayesian estimation</a>, <a href="#">Ridge regression</a>, <a href="#">Vector autoregres "
"docPreview" => "<b>We modeled long memory with just one lag!</b><br><span>2023-09 | Journal articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://doi.org/10.1016/j.jeconom.2023.04.010" target="_blank">We modeled long memory with just one lag!</a> <a href="https://doi.org/10.1016/j.jeconom.2023.04.010" target="_blank">We modeled long memory with "
]
+lang: "en"
+"_type": "_doc"
+"_score": 8.604398
+"parent": null
}
